README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file - rmarkdown::render('README.Rmd', output_format = 'github_document', output_file = 'README.md') -->

```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "images/"
)
is_online = curl::has_internet()
```

# Geocomputation with R  

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## Introduction

This repository hosts the code underlying Geocomputation with R, a book by [Robin Lovelace](https://www.robinlovelace.net/), [Jakub Nowosad](https://jakubnowosad.com/), and [Jannes Muenchow](https://github.com/jannes-m).
If you find the contents useful, please [cite it](https://github.com/geocompx/geocompr/raw/main/CITATION.bib) as follows:

> Lovelace, Robin, Jakub Nowosad and Jannes Muenchow (2025). Geocomputation with R. The R Series. CRC Press.

To learn more about the second edition of the book, see the ["Second edition of Geocomputation with R is complete" blog post](https://geocompx.org/post/2024/geocompr2-bp3/).

The first version of the book has been published by [CRC Press](https://www.crcpress.com/9781138304512) in the [R Series](https://www.routledge.com/Chapman--HallCRC-The-R-Series/book-series/CRCTHERSER) and can be viewed online at [bookdown.org](https://bookdown.org/robinlovelace/geocompr/).
Read the latest version at [r.geocompx.org](https://r.geocompx.org/).

<!-- 
### Note: we are actively working on the Second Edition 🏗

<details>
  <summary>Summary of the changes</summary>

Since commencing work on the Second Edition in September 2021 much has changed, including:

- Replacement of `raster` with `terra` in Chapters 1 to 7 (see commits related to this update [here](https://github.com/geocompx/geocompr/search?q=terra&type=commits)) 
- Update of Chapter 7 to include mention alternative ways or reading-in OSM data in [#656](https://github.com/geocompx/geocompr/pull/656)
- Refactor build settings so the book builds on Docker images in the [geocompr/docker](https://github.com/geocompx/docker) repo
- Improve the experience of using the book in Binder (ideal for trying out the code before installing or updating the necessary R packages), as documented in issue [#691](https://github.com/geocompx/geocompr/issues/691) (thanks to [yuvipanda](https://github.com/yuvipanda))
- Improved communication of binary spatial predicates in Chapter 4 (see [#675](https://github.com/geocompx/geocompr/pull/675))
- New section on the links between subsetting and clipping (see [#698](https://github.com/geocompx/geocompr/pull/698)) in Chapter 5
- New [section](https://r.geocompx.org/spatial-operations.html#de-9im-strings) on the dimensionally extended 9-intersection model (DE-9IM)
- New [chapter](https://r.geocompx.org/raster-vector.html) on raster-vector interactions split out from Chapter 5
- New [section](https://r.geocompx.org/spatial-class.html#the-sfheaders-package) on the **sfheaders** package
- New [section](https://r.geocompx.org/spatial-class.html#s2) in Chapter 2 on spherical geometry engines and the **s2** package
- Replacement of code based on the old **mlr** package with code based on the new **mlr3** package, as described in a huge [pull request](https://github.com/geocompx/geocompr/pull/771)
- Adaptation to changes in the PROJ library, using WKT2 and SRID format for defining coordinate reference systems
- Update to most figures using version 4 of the **tmap** package, with a different syntax and new features for improved customization and aesthetics
- Several new graphs to enhance understanding, such as one illustrating the process of creating an `sf` object
- Rewritten and expanded the "Bridges to GIS software" chapter, including new packages like **qgisprocess**, **Rsagacmd**, and **rgrass**
- Rewritten the "Transportation" chapter, introducing new sections on routes and route networks
- New book parts related to the creation of geographic metadata and connecting R with cloud services
<!-- Todo: update this bullet point (Rl 2023-03) -->

<!-- Todo: add news file? (RL 2021-11) -->
<!-- See NEWS.md for a summary of the changes. -->
<!--
See [https://github.com/geocompx/geocompr/compare/1.9...main](https://github.com/geocompx/geocompr/compare/1.9...main#files_bucket) for a continuously updated summary of the changes to date.
This shows 20k+ lines of code/prose added, lots of refactoring!
</details> -->

Contributions are very welcome.

## Contributing

We encourage contributions on any part of the book, including:

- improvements to the text, e.g., clarifying unclear sentences, fixing typos (see guidance from [Yihui Xie](https://yihui.org/en/2013/06/fix-typo-in-documentation/));
- changes to the code, e.g., to do things in a more efficient way; 
- suggestions on content (see the project's [issue tracker](https://github.com/geocompx/geocompr/issues));
- improvements to and alternative approaches in the Geocompr solutions booklet hosted at [r.geocompx.org/solutions](https://r.geocompx.org/solutions) (see a blog post on how to update solutions in files such as [_01-ex.Rmd](https://github.com/geocompx/geocompr/blob/main/_01-ex.Rmd) [here](https://geocompx.org/post/2022/geocompr-solutions/))

See [our-style.md](https://github.com/geocompx/geocompr/blob/main/misc/our-style.md) for the book's style.

```{r contributors, include=FALSE}
contributors = source("code/list-contributors.R")[[1]]
# save for future reference:
readr::write_csv(contributors, "extdata/contributors.csv")
# table view:
# knitr::kable(contributors, caption = "Contributors to Geocomputation with R")
# text view
c_txt = contributors$name
c_url = contributors$link
c_rmd = paste0("[", c_txt, "](", c_url, ")")
contributors_text = paste0(c_rmd, collapse = ", ")
```

Many thanks to all contributors to the book so far via GitHub (this list will update automatically): `r contributors_text`.

During the project we aim to contribute 'upstream' to the packages that make geocomputation with R possible.
This impact is recorded in [`our-impact.csv`](https://github.com/geocompx/geocompr/blob/main/misc/our-impact.csv).

## Downloading the source code

The recommended way to get the source code underlying Geocomputation with R on your computer is by cloning the repo.
You can can that on any computer with [Git](https://github.com/git-guides/install-git) installed with the following command:

```bash
git clone https://github.com/geocompx/geocompr.git
```

An alternative approach, which we recommend for people who want to contribute to open source projects hosted on GitHub, is to install the [`gh` CLI tool](https://github.com/cli/cli#installation).
From there cloning a fork of the source code, that you can change and share (including with Pull Requests to improve the book), can be done with the following command:

```bash
gh repo fork geocompx/geocompr # (gh repo clone geocompx/geocompr # also works)
```

Both of those methods require you to have Git installed.
If not, you can download the book's source code from the URL https://github.com/geocompx/geocompr/archive/refs/heads/main.zip .
Download/unzip the source code from the R command line to increase reproducibility and reduce time spent clicking around:

```{r dl-unzip}
#| eval=FALSE
u = "https://github.com/geocompx/geocompr/archive/refs/heads/main.zip"
f = basename(u)
download.file(u, f)        # download the file
unzip(f)                   # unzip it
file.rename(f, "geocompr") # rename the directory
rstudioapi::openProject("geococompr") # or open the folder in vscode / other IDE
```

## Reproducing the book in R/RStudio/VS Code

To ease reproducibility, we created the `geocompkg` package.
Install it with the following commands:

```{r readme-install-github}
#| eval=FALSE
install.packages("remotes")
# To reproduce the first Part (chapters 1 to 8):
install.packages("geocompkg", repos = c("https://geocompr.r-universe.dev", "https://cloud.r-project.org"), dependencies = TRUE, force = TRUE)
```

Installing `geocompkg` will also install core packages required for reproducing **Part I of the book** (chapters 1 to 8). 
Note: you may also need to install [system dependencies](https://github.com/r-spatial/sf#installing) if you're running Linux (recommended) or Mac operating systems.
You also need to have the [**remotes**](https://github.com/r-lib/remotes/) package installed:

To reproduce book **in its entirety**, run the following command (which installs additional 'Suggests' packages, this may take some time to run!):

```{r readme-install-github-2, message=FALSE, results='hide'}
#| eval=FALSE
# Install packages to fully reproduce book (may take several minutes):
options(repos = c(
  geocompx = "https://geocompx.r-universe.dev",
  cran = "https://cloud.r-project.org/"
))
# From geocompx.r-universe.dev (recommended):
install.packages("geocompkg", dependencies = TRUE)

# Alternatively from GitHub:
remotes::install_github("geocompx/geocompkg", dependencies = TRUE)
```

You need a recent version of the GDAL, GEOS, PROJ and udunits libraries installed for this to work on Mac and Linux.
See the **sf** package's [README](https://github.com/r-spatial/sf) for information on that.
After the dependencies have been installed you should be able to build and view a local version the book with:

```{r readme-render-book}
#| eval=FALSE
# Change this depending on where you have the book code stored:
rstudioapi::openProject("~/Downloads/geocompr")
 # or code /location/of/geocompr in the system terminal
 # or cd /location/of/geocompr then R in the system terminal, then:
bookdown::render_book("index.Rmd") # to build the book
browseURL("_book/index.html")      # to view it
# Or, to serve a live preview the book and observe impact of changes:
bookdown::serve_book(".")
```

<!-- The code associated with each chapter is saved in the `code/chapters/` folder. -->
<!-- `source("code/chapters/07-transport.R")` runs run the code chunks in chapter 7, for example. -->
<!-- These R scripts are generated with the follow command which wraps `knitr::purl()`: -->

```{r gen-code, results='hide', echo=FALSE}
#| eval=FALSE
geocompkg:::generate_chapter_code()
```

## Geocompr in a devcontainer

A great feature of VS Code is [devcontainers](https://code.visualstudio.com/docs/remote/containers), which allow you to develop in an isolated Docker container.
If you have VS Code and the necessary dependencies installed on your computer, you can build Geocomputation with R in a devcontainer as shown below (see [#873](https://github.com/geocompx/geocompr/issues/873) for details):

![](https://user-images.githubusercontent.com/1825120/193398022-bbcfbfda-5d57-4c57-8db3-ed1fdb4a07be.png)

## Geocompr in Binder

For many people the quickest way to get started with Geocomputation with R is in your web browser via Binder.
To see an interactive RStudio Server instance click on the following button, which will open [mybinder.org](https://mybinder.org/v2/gh/geocompx/geocompr/main?urlpath=rstudio) with an R installation that has all the dependencies needed to reproduce the book:

[![Launch Rstudio Binder](http://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/geocompx/geocompr/main?urlpath=rstudio)

You can also have a play with the repository in RStudio Cloud by clicking on this link (requires log-in):

[![Launch Rstudio Cloud](images/cloud.png)](https://rstudio.cloud/project/1642300)

## Geocomputation with R in a Docker container

See the [geocompx/docker](https://github.com/geocompx/docker) repository for details.

## Reproducing this README

To reduce the book's dependencies, scripts to be run infrequently to generate input for the book are run on creation of this README.

The additional packages required for this can be installed as follows:

```{r extra-pkgs, message=FALSE, eval=FALSE}
source("code/extra-pkgs.R")
```

With these additional dependencies installed, you should be able to run the following scripts, which create content for the book, that we've removed from the main book build to reduce package dependencies and the book's build time:

```{r source-readme, eval=FALSE}
source("code/01-cranlogs.R")
source("code/sf-revdep.R")
source("code/09-urban-animation.R")
source("code/09-map-pkgs.R")
```

Note: the `.Rproj` file is configured to build a website not a single page.
To reproduce this [README](https://github.com/geocompx/geocompr/blob/main/README.Rmd) use the following command:

```{r render-book, eval=FALSE}
rmarkdown::render("README.Rmd", output_format = "github_document", output_file = "README.md")
```


```{r scripts,  eval=FALSE, echo=FALSE}
# We aim to make every script in the `code` folder reproducible.
# To check they can all be reproduced run the following:
# Aim: test reproducibility of scripts
script_names = list.files("code", full.names = T)
avoid = "pkgs|anim|us|saga|sliver|tsp|parti|polycent|cv|svm|data|location|eco|rf|cran|hex"
dontrun = grepl(avoid, script_names)
script_names = script_names[!dontrun]
counter = 0
for(i in script_names[45:length(script_names)]) {
  counter = counter + 1
  print(paste0("Script number ", counter, ": ", i))
  source(i)
}
```


<!-- ## Book statistics -->

<!-- An indication of the book's progress over time is illustrated below (to be updated roughly every week as the book progresses). -->

```{r gen-stats, echo=FALSE, message=FALSE, warning=FALSE, eval=FALSE}
# source("code/generate-chapter-code.R")
book_stats = readr::read_csv("extdata/word-count-time.csv",
                             col_types = ("iiDd"))

# to prevent excessive chapter count
if (Sys.Date() > max(book_stats$date) + 5) {
  book_stats_new = geocompkg:::generate_book_stats()
  book_stats = bind_rows(book_stats, book_stats_new)
  readr::write_csv(book_stats, "extdata/word-count-time.csv")
}
book_stats = dplyr::filter(book_stats, chapter <= 15) 
library(ggplot2)
book_stats$chapter = formatC(book_stats$chapter, width = 2, format = "d", flag = "0")
book_stats$chapter = fct_rev(as.factor(book_stats$chapter))
book_stats$n_pages = book_stats$n_words / 300
```

```{r bookstats, warning=FALSE, echo=FALSE, fig.width=8, fig.height=5, eval=FALSE}
ggplot(book_stats) +
  geom_area(aes(date, n_pages, fill = chapter), position = "stack") +
  ylab("Estimated number of pages") +
  xlab("Date") + 
  scale_x_date(date_breaks = "2 month",
               limits = c(min(book_stats$date), as.Date("2018-10-01")),
               date_labels = "%b %Y") +
  coord_cartesian(ylim = c(0, 350))
```

<!-- Book statistics: estimated number of pages per chapter over time. -->

## Citations

The main packages used in this book are cited from `packages.bib`.
Other citations are stored online using Zotero.

If you would like to add to the references, please use Zotero, join the [open group](https://www.zotero.org/groups/418217/energy-and-transport) add your citation to the open [geocompr library](https://www.zotero.org/groups/418217/energy-and-transport/items/collectionKey/9K6FRP6N).

We use the following citation key format:

```
[auth:lower]_[veryshorttitle:lower]_[year]
```

This can be set from inside Zotero desktop with the Better Bibtex plugin installed (see [github.com/retorquere/zotero-better-bibtex](https://github.com/retorquere/zotero-better-bibtex)) by selecting the following menu options (with the shortcut `Alt+E` followed by `N`), and as illustrated in the figure below:

```
Edit > Preferences > Better Bibtex
```

![](images/zotero-settings.png)

Zotero settings: these are useful if you want to add references.

When you export the citations as a .bib file from Zotero, use the  `Better BibTex` (not `BibLaTeX`) format.

We use Zotero because it is a powerful open source reference manager that integrates well with citation tools in VS Code and RStudio.